1. Field of the Invention
The present invention relates to estimating component concentrations of a mixture. More particularly, the present invention relates to a method and apparatus for estimating a concentration of a specific component included in a mixture spectrum using a plurality of local calibration models.
2. Description of the Related Art
In a method generally used to estimate a concentration of a specific component from a mixture spectrum, for example, in a multivariate analysis method such as principal component regression, a global calibration model, which is a regression model, is generated from a calibration data set. A concentration of a specific component is then estimated from a spectrum obtained using the global calibration model. However, in a process of obtaining the calibration data set for generating the global calibration model, noise is generated. In general, since amplitudes or characteristics of the noise vary throughout the calibration data set, the calibration data set can conceptually be divided into a plurality of small groups according to the amplitudes or characteristics of the noise. In this case, when the global calibration model is generated from the calibration data set, a noise characteristic of one small group may be propagated to another small group. For example, even if there is no noise in a particular small group of a calibration data set, when a global calibration model is generated from the calibration data set, a prediction error may be caused by the propagation of noise from another small group.
FIGS. 1A and 1B are graphs illustrating a prediction error generated when estimating a concentration using a general multivariate analysis method.
More specifically, when a single global calibration model is applied, one of two regressive lines 110 and 120 may be obtained, as shown in FIG. 1A. If the regressive line 110 is obtained, on the basis of a value of an independent variable x, the global calibration model may not be properly applied to a small group of an area 140, as shown in FIG. 1B. Also, if the regressive line 120 is obtained, on the basis of a value of an independent variable x, the global calibration model may not be properly applied to a small group of an area 130, as shown in FIG. 1B.